What is he best known for?
The fields of study he is best known for:
- Mathematical analysis
- Eigenvalues and eigenvectors
- Algebra
His primary scientific interests are in Eigenvalues and eigenvectors, Applied mathematics, Mathematical analysis, Algebra and Control theory.
Volker Mehrmann has researched Eigenvalues and eigenvectors in several fields, including Matrix, Numerical analysis and Polynomial.
His research in Applied mathematics intersects with topics in Differential algebraic equation, Canonical form, Reduction, Descriptor systems and Differential equation.
As a part of the same scientific study, he usually deals with the Mathematical analysis, concentrating on Linear subspace and frequently concerns with Invariant and Algebraic equation.
His Algebra research includes elements of Symplectic group and Compressed sensing.
His Control theory research includes themes of Software development and Fortran.
His most cited work include:
- Differential-Algebraic Equations: Analysis and Numerical Solution (676 citations)
- Dimension Reduction of Large-Scale Systems (323 citations)
- The Autonomous Linear Quadratic Control Problem (290 citations)
What are the main themes of his work throughout his whole career to date?
Volker Mehrmann mainly investigates Applied mathematics, Eigenvalues and eigenvectors, Mathematical analysis, Matrix and Numerical analysis.
His Applied mathematics research focuses on Mathematical optimization and how it relates to Partial differential equation.
His biological study spans a wide range of topics, including Hamiltonian matrix and Pure mathematics.
His studies deal with areas such as Algebraic equation and Linear subspace as well as Mathematical analysis.
The concepts of his Matrix study are interwoven with issues in Canonical form, Hermitian matrix and Combinatorics.
His research in Descriptor systems, Controllability and Observability are components of Control theory.
He most often published in these fields:
- Applied mathematics (29.92%)
- Eigenvalues and eigenvectors (23.88%)
- Mathematical analysis (22.83%)
What were the highlights of his more recent work (between 2016-2021)?
- Applied mathematics (29.92%)
- Eigenvalues and eigenvectors (23.88%)
- Matrix (17.06%)
In recent papers he was focusing on the following fields of study:
His main research concerns Applied mathematics, Eigenvalues and eigenvectors, Matrix, Robustness and Mathematical optimization.
His studies in Applied mathematics integrate themes in fields like Discretization, Numerical analysis, Exponential stability and Algebraic number.
Volker Mehrmann works mostly in the field of Eigenvalues and eigenvectors, limiting it down to topics relating to Linear algebra and, in certain cases, Matrix pencil.
Volker Mehrmann has included themes like Canonical form, Pure mathematics and Hamiltonian in his Matrix study.
His Robustness study also includes fields such as
- Transfer function that connect with fields like Topology and Inequality,
- Solution set which intersects with area such as Discrete time and continuous time, Coordinate system and Algebra,
- Linear matrix inequality which is related to area like Passivity,
- Linear system that intertwine with fields like Main diagonal and Sparse matrix,
- Coefficient matrix and related Algorithm.
His Mathematical optimization study integrates concerns from other disciplines, such as Flow, Pipeline, Partial differential equation, Set and Computation.
Between 2016 and 2021, his most popular works were:
- The Shifted Proper Orthogonal Decomposition: A Mode Decomposition for Multiple Transport Phenomena (63 citations)
- On Structure-Preserving Model Reduction for Damped Wave Propagation in Transport Networks (40 citations)
- Linear port-Hamiltonian descriptor systems (31 citations)
In his most recent research, the most cited papers focused on:
- Mathematical analysis
- Algebra
- Eigenvalues and eigenvectors
Volker Mehrmann spends much of his time researching Applied mathematics, Topology, Nonlinear system, Dynamical systems theory and Invariant.
His Applied mathematics research is multidisciplinary, relying on both Partial differential equation and Minification.
Within one scientific family, he focuses on topics pertaining to Representation under Nonlinear system, and may sometimes address concerns connected to Differentiable function, Hamiltonian, Lyapunov function and Polynomial.
The study incorporates disciplines such as Equivalence, Descriptor systems and Stability radius in addition to Dynamical systems theory.
His studies deal with areas such as Parameter dependent, Regularization, Canonical form, Hermitian matrix and Scaling as well as Invariant.
His Mathematical analysis study frequently involves adjacent topics like Algebra.
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